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dsfox/worlds-largest-cargo-airports

Largest Aviation Hubs — Cargo Airports The world's busiest airports by air cargo (metric tonnes). Part of globalhubs.top — datasets of the world's largest freight transport hubs across three dimensions: maritime, aviation and land. (Passengers are out of scope.) Files File Description airports.csv One row per airport (UTF-8, comma-separated) airports.parquet Same data in Apache Parquet CITATION.cff Citation metadata (GitHub "Cite this repository")… See the full description on the dataset page: https://huggingface.co/datasets/dsfox/worlds-largest-cargo-airports.

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Dataset Card

Largest Aviation Hubs — Cargo Airports

The world's busiest airports by air cargo (metric tonnes). Part of globalhubs.top — datasets of the world's largest freight transport hubs across three dimensions: maritime, aviation and land. (Passengers are out of scope.)

Files

File	Description
`airports.csv`	One row per airport (UTF-8, comma-separated)
`airports.parquet`	Same data in Apache Parquet
`CITATION.cff`	Citation metadata (GitHub "Cite this repository")

Schema

Column	Type	Description
`rank`	int	Rank by air cargo throughput
`airport_name`	string	Airport name
`iata`	string	IATA code
`icao`	string	ICAO code
`unlocode`	string	UN/LOCODE (UNECE) — 5-char location code, e.g. `HKHKG`; blank if none
`city`	string	City
`country`	string	Country
`country_iso2`	string	ISO 3166-1 alpha-2 country code
`region`	string	Geographic region
`latitude`	float	Latitude (WGS84)
`longitude`	float	Longitude (WGS84)
`cargo_tonnes`	int	Air cargo throughput, metric tonnes (freight + mail)
`yoy`	float	Year-over-year change in cargo, percent
`operator`	string	Airport operator (where known)
`website`	string	Official website (verified; blank if none)
`address`	string	Postal address of the airport (`n/d` if not confidently found)

Coverage

Top 50 airports by air cargo throughput.

Usage

python

import pandas as pd
df = pd.read_csv("airports.csv")              # or pd.read_parquet("airports.parquet")
print(df.sort_values("rank").head(10)[["rank", "airport_name", "iata", "country", "cargo_tonnes", "yoy"]])

python

# Read the Parquet straight from the Hugging Face hub (no manual download)
import pandas as pd
df = pd.read_parquet("hf://datasets/dsfox/worlds-largest-cargo-airports/airports.parquet")

sql

-- DuckDB: query the Hugging Face Parquet in place
INSTALL httpfs; LOAD httpfs;
SELECT rank, airport_name, iata, country, cargo_tonnes
FROM 'hf://datasets/dsfox/worlds-largest-cargo-airports/airports.parquet'
ORDER BY rank LIMIT 10;

Notebooks (Kaggle): starter · EDA.

Related datasets

Related open CC0 datasets in the globalhubs.top series: container ports · inland freight hubs · container shipping lines · air-cargo carriers · freight railways · logistics companies. See also humans.top — the world's most influential people.

License

Released under CC0 1.0 — public domain. Free for any use, including AI / LLM training. No attribution required (a link back to globalhubs.top is always welcome).

How to cite

Author: Dmitry Golubnichiy (ORCID 0009-0007-3307-2202). Cite via the DOI 10.5281/zenodo.21058130 (resolves to the latest version), or:

bibtex

@misc{globalhubs_aviation,
  title  = {Largest Aviation Hubs — Cargo Airports (open dataset)},
  author = {Golubnichiy, Dmitry},
  year   = {2026},
  doi    = {10.5281/zenodo.21058130},
  url    = {https://globalhubs.top},
  note   = {CC0 1.0 (public domain)}
}

Versioning

v1 — initial release.